An analysis of the effects of a peer mentor program and other factors on HIV patients' retention in care and clinical outcomes at Thomas Street Health Clinic, Houston Texas

Research examining programs designed to retain patients in health care focus on repeated interactions between outreach workers and patients (Bradford et al. 2007; Cheever 2007). The purpose of this study was to determine if patients who are peer-mentored at their intake exam remain in care longer and attend more physicians' visits than those who were not mentored. Using patients' medical records and a previously created mentor database, the study determined how many patients attended their intake visit but subsequently failed to establish regular care. The cohort study examined risk factors for establishing care, determined if patients lacking a peer mentor failed to establish care more than peer mentor assisted patients, and subsequently if peer mentored patients had better health outcomes. The sample consists of 1639 patients who were entered into the Thomas Street Patient Mentor Database between May 2005 and June 2007. The assignment to the mentored group was haphazardly conducted based on mentor availability. The data from the Mentor Database was then analyzed using descriptive statistical software (SPSS version 15; SPSS Inc., Chicago, Illinois, USA). Results indicated that patients who had a mentor at intake were more likely to return for primary care HIV visits at 90 and 180 days. Mentored patients also were more likely to be prescribed ART within 180 days from intake. Other risk factors that impacted remaining in care included gender, previous care status, time from diagnosis to intake visit, and intravenous drug use. Clinical health outcomes did not differ significantly between groups. This supports that mentoring did improve outcomes. Continuing to use peer-mentoring programs for HIV care may help in increasing retention of patients in care and improving patients' health in a cost effective manner. Future research on the effects of peer mentoring on mentors, and effects of concordance of mentor and patient demographics may help to further improve peer-mentoring programs. ^

Relationship between parental feeding practices and weight status in a lower socioeconomic pre-school population

High prevalence of overweight and obesity among preschool children in the low income population is consistently documented in research with one of every seven low-income, preschool-aged children classified as obese. Parental feeding practices have the potential to be contributing factors to the obesity epidemic. However, the impact of parental feeding practices on obesity in preschool age children has not been well explored. The purpose of this study was to determine relationships between the parental feeding practices of using dessert, sweets or candy as a reward for finishing foods, restricting dessert if the child does not finish their plate at dinner, asking the child to consume everything on their plate at dinner, and having family dinners to obesity in low income, preschool age children.^ A cross-sectional secondary data analysis was completed using the STATA 11 statistical software. Descriptive statistics were completed to summarize demographic and BMI data of participants, as well as parental feeding behavior variables. Pearson’s correlation was implemented to determine a correlation between parental feeding behavior variables and BMI z scores. Predictive relationships between the variables were explored through multivariable linear regression analysis. Regression analyses were also completed factoring in the confounders of gender, age, and ethnicity.^ Results revealed (1) no significant correlations or predictive trends between the use of rewards, forced consumption, or family dinner and BMI in low income preschool age children, and (2) a significant negative correlation and predictive trend between restriction of desserts and BMI in low income preschool age children. Since the analysis supported the null hypothesis for the practices of reward use, forced consumption, and family dinner, these practices are not considered risk factors for obese level BMIs. The inverse association found for practice of restriction and BMI suggests it is unnecessary to discourage parents from using restriction. Limitations of the study included the sample size, reliability of the answers provided on the Healthy Home Survey by participant guardians, and generalizability of the sample to the larger population.^

Food availability in the home and dietary intake of the Harris County Department of Education Head Start population

Background. The prevalence of obesity and overweight children has been an ongoing health epidemic in the US for the last several decades. The problem has consistently worsened and has disproportionately been the most prevalent among low socioeconomic status (SES) populations. Food availability in the home has been suggested to be a potential factor related to overweight and obesity, as availability is likely associated with intake. Food availability of low SES preschool aged children has not been well examined. The purpose of this study was to explore the food environment of the Harris County Department of Education (HCDE) Head Start population, and describe reported frequency of intake of particular food groups. The effect of food availability on reported intake was also examined.^ Methods. This was a cross-sectional study of secondary data analysis. Data obtained from 17 HCDE Head Start Centers was analyzed using PASW 18 Statistical Software. Demographic analyses included population, age, gender, race, parent occupation, type of home, and language spoken in the home. Descriptive statistics included reported availability of foods in the home as well as frequency of intake.^ Regression analysis examined the relationship of availability of foods on intake. The food categories included were: dark leafy green and orange vegetables, other vegetables, fruits, soda, salty snacks, and sweet snacks. For both vegetable categories reported intake of fresh, frozen, and canned vegetables were included. For the fruit category, intake of fresh, frozen, canned, and dried fruits were reported.^ Results. Results showed that 90-95% of parents reported having vegetables and fruits available in the home. However, the only significant relationship between availability and intake was for fresh fruit and dried fruit. No associations were seen among the vegetable groups. Other vegetables (bell peppers, eggplant, tomatoes, onions, iceberg lettuce, asparagus) that were frozen, approached significance for availability on intake, however once adjusted for confounders the relationship was no longer present. Among soda, salty snacks, and sweet snacks the only significant relationship was seen for soda availability and intake. Salty snacks and sweet snacks presence in the home was not a predictor of increased frequency of intake.^ Conclusions. This research supported the hypothesis that availability of foods has an impact on intake for fresh fruits, dried fruits and soda. No associations were seen for vegetables, salty snacks and sweet snacks. Additionally, most of the parents reported having fruits and vegetables in the home, but reported intakes were not meeting the Dietary Guidelines for Americans recommendations. Strengths of the study included the large sample size taken from numerous HCDE Head Start Centers. Limitations included questionable reliability of participant’s responses, ability to generalize to other populations, and the use of secondary data rather than prospectively collected data.^

A comparison of worker risk of injury while working on fully automated side loaders and other residential collection trucks at a large solid waste collection company

The study aim was to determine whether using automated side loader (ASL) trucks in higher proportions compared to other types of trucks for residential waste collection results in lower injury rates (from all causes). The primary hypothesis was that the risk of injury to workers was lower for those who work with ASL trucks than for workers who work with other types of trucks used in residential waste collection. To test this hypothesis, data were collected from one of the nation’s largest companies in the solid waste management industry. Different local operating units (i.e. facilities) in the company used different types of trucks to varying degrees, which created a special opportunity to examine refuse collection injuries and illnesses and the risk reduction potential of ASL trucks.^ The study design was ecological and analyzed end-of-year data provided by the company for calendar year 2007. During 2007, there were a total of 345 facilities which provided residential services. Each facility represented one observation.^ The dependent variable – injury and illness rate, was defined as a facility’s total case incidence rate (TCIR) recorded in accordance with federal OSHA requirements for the year 2007. The TCIR is the rate of total recordable injury and illness cases per 100 full-time workers. The independent variable, percent of ASL trucks, was calculated by dividing the number of ASL trucks by the total number of residential trucks at each facility.^ Multiple linear regression models were estimated for the impact of the percent of ASL trucks on TCIR per facility. Adjusted analyses included three covariates: median number of hours worked per week for residential workers; median number of months of work experience for residential workers; and median age of residential workers. All analyses were performed with the statistical software, Stata IC (version 11.0).^ The analyses included three approaches to classifying exposure, percent of ASL trucks. The first approach included two levels of exposure: (1) 0% and (2) >0 - <100%. The second approach included three levels of exposure: (1) 0%, (2) ≥ 1 - < 100%, and (3) 100%. The third approach included six levels of exposure to improve detection of a dose-response relationship: (1) 0%, (2) 1 to <25%, (3) 25 to <50%, (4) 50 to <75%, (5) 75 to <100%, and (6) 100%. None of the relationships between injury and illness rate and percent ASL trucks exposure levels was statistically significant (i.e., p<0.05), even after adjustment for all three covariates.^ In summary, the present study shows that there is some risk reduction impact of ASL trucks but not statistically significant. The covariates demonstrated a varied yet more modest impact on the injury and illness rate but again, none of the relationships between injury and illness rate and the covariates were statistically significant (i.e., p<0.05). However, as an ecological study, the present study also has the limitations inherent in such designs and warrants replication in an individual level cohort design. Any stronger conclusions are not suggested.^

Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

A full pedigree based method for the statistical assessment of genetic anticipation

Genetic anticipation is defined as a decrease in age of onset or increase in severity as the disorder is transmitted through subsequent generations. Anticipation has been noted in the literature for over a century. Recently, anticipation in several diseases including Huntington's Disease, Myotonic Dystrophy and Fragile X Syndrome were shown to be caused by expansion of triplet repeats. Anticipation effects have also been observed in numerous mental disorders (e.g. Schizophrenia, Bipolar Disorder), cancers (Li-Fraumeni Syndrome, Leukemia) and other complex diseases. ^ Several statistical methods have been applied to determine whether anticipation is a true phenomenon in a particular disorder, including standard statistical tests and newly developed affected parent/affected child pair methods. These methods have been shown to be inappropriate for assessing anticipation for a variety of reasons, including familial correlation and low power. Therefore, we have developed family-based likelihood modeling approaches to model the underlying transmission of the disease gene and penetrance function and hence detect anticipation. These methods can be applied in extended families, thus improving the power to detect anticipation compared with existing methods based only upon parents and children. The first method we have proposed is based on the regressive logistic hazard model. This approach models anticipation by a generational covariate. The second method allows alleles to mutate as they are transmitted from parents to offspring and is appropriate for modeling the known triplet repeat diseases in which the disease alleles can become more deleterious as they are transmitted across generations. ^ To evaluate the new methods, we performed extensive simulation studies for data simulated under different conditions to evaluate the effectiveness of the algorithms to detect genetic anticipation. Results from analysis by the first method yielded empirical power greater than 87% based on the 5% type I error critical value identified in each simulation depending on the method of data generation and current age criteria. Analysis by the second method was not possible due to the current formulation of the software. The application of this method to Huntington's Disease and Li-Fraumeni Syndrome data sets revealed evidence for a generation effect in both cases. ^